Login / Signup

Traditional East Asian Herbal Medicine for Amyotrophic Lateral Sclerosis: A Scoping Review.

Won Joo SuhYuna SeoChul JinSeung-Yeon ChoSeong-Uk ParkWoo-Sang JungSang-Kwan MoonJung-Mi ParkChang-Nam KoSeungwon KwonKi-Ho Cho
Published in: Evidence-based complementary and alternative medicine : eCAM (2021)
This study aimed to analyze and summarize the existing evidence regarding herbal medicine treatments for amyotrophic lateral sclerosis (ALS). Studies on herbal medicine treatment in patients with ALS were searched within English, Chinese, Japanese, and Korean databases up to July 31, 2021. In the selected studies, we collected the following information: the first author, year of publication, country, language, study methodology, sample size, demographic characteristics of the study participants, disease duration, diagnostic criteria, treatment method, treatment periods, evaluation tools, results, and side effects. The organized data were classified and analyzed narratively. This study included 59 studies. The first clinical study on the effect of herbal medicine was published in 1995; moreover, most studies were conducted in China. Among the 59 selected studies, 47.5% were observational studies, including case reports and case series. Moreover, there was one meta-analysis. The El Escorial criteria were the most commonly used diagnostic criterion for ALS; moreover, the ALS functional rating scale was the most common evaluation tool. Buzhongyiqitang, Sijunzitangjiawei, and Jianpiyifeitang were the most commonly used herbal medicines, with anti-inflammatory, protein aggregation, and anti-oxidant effects. There remain evidence of gaps in the effectiveness of herbal medicine for ALS. To allow effective treatment of patients with ALS using herbal medicine, large-scale and rigorously designed high-quality clinical studies should be performed.
Keyphrases
  • amyotrophic lateral sclerosis
  • systematic review
  • anti inflammatory
  • randomized controlled trial
  • small molecule
  • combination therapy
  • machine learning
  • social media
  • binding protein
  • deep learning
  • double blind